Instructions to use nomnomnomz/last with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nomnomnomz/last with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nomnomnomz/last", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e822ccf0ba7c62cc965e96294320daba29ce94aab1cc45d3f14046c8713fca9e
- Size of remote file:
- 335 MB
- SHA256:
- b852dcbce016636556ea2204bccef50ecca2379e290e5660746949c3b9ff2c39
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